Hermes Agent Setup
After installing, the goal is one clean working chat: connect one model provider, check health, run a small task, and confirm the session resumes. Add messaging, cron, skills, and voice only after that works — the same order the official quickstart recommends.
On a fresh install, hermes setup offers three modes: Quick Setup (Nous Portal sign-in), Full Setup (walk through every provider and tool yourself), and Blank Slate (only a model plus file and terminal tools; everything else off until you enable it). Hermes Desktop has its own first-run onboarding for connecting a provider.
Checked against the official quickstart on September 26, 2026.
Connect Your Model Provider
Pick one path now; you can add others later and switch with /model. For help choosing, see Hermes models and providers; for plans, see Nous Portal.
Option A: Nous Portal (Quick Setup)
Official recommendationBrowser login, no API keys. The free plan covers free models; paid plans (from $20/month) add the wider catalog and the Tool Gateway for web search, image generation, text-to-speech, and cloud browser tools.
$hermes setup --portal
Opens a browser sign-in; the token is stored in ~/.hermes/auth.json. On a headless server, see the official OAuth-over-SSH guide.
Option B: API key or an existing subscription
Pay-As-You-GoPaste an API key (OpenRouter, Anthropic, OpenAI, Google, DeepSeek, and many more), or sign in with a plan you already pay for — ChatGPT/Codex, Claude Max with extra usage credits, GitHub Copilot, or SuperGrok — from the hermes model menu.
# Pick a provider and sign in or paste a key$hermes model$# Or store a key directly (written to ~/.hermes/.env)$hermes config set OPENROUTER_API_KEY sk-or-v1-...
Claude Pro cannot be used this way; use an Anthropic API key instead. Details per plan are on the models page.
Option C: Local Offline Models (Ollama / vLLM)
Local InferenceRun inference on your own hardware. Hermes needs a tool-calling model with at least a 64K context window, and many local servers default lower. Cloud tools you enable can still send data off-device.
# Serve a tool-capable model with a 64K+ context window,# e.g. Ollama with -c 65536 or llama.cpp with --ctx-size 65536$# Point Hermes at the local server$hermes model# Choose "Custom endpoint"; URL: http://localhost:11434/v1 (Ollama)# Enter the exact model name; leave the API key blank
Hermes can also download and run llama.cpp models for you from Desktop (Settings → Providers → Local Models; canary builds or the --local flag).
Select Your Primary Model (hermes model)
Run the interactive model selector at any time to switch providers and select your default model:
$hermes model
Hermes Agent stores active model configurations in ~/.hermes/config.yaml and environment keys in ~/.hermes/.env. You can inspect or edit these files directly with your preferred editor. On native Windows, the default data folder is %LOCALAPPDATA%\hermes; custom profiles use their own folder.
Run Health Checks (hermes doctor)
Check configuration, dependencies, and service health before testing your first prompt:
$hermes doctor
Execute Your First Agent Prompt
Test interactive chat mode or run a direct one-shot CLI prompt to verify tool execution:
$hermes # classic CLI$hermes --tui # full-screen TUI
The banner should show your provider and model. Ask for something checkable, such as “summarize this repo in 5 bullets”, and continue for more than one turn.
$hermes chat --oneshot -q "Inspect current directory git status"
Answers the query and exits. Without --oneshot, -q now seeds an interactive session instead.
$hermes --continue # resumes your most recent session
If resume fails, check you are in the same profile (hermes sessions list).
Where to Go From Here
Once a plain chat works, add one layer at a time. Messaging runs through the gateway — Telegram or Discord.
Models & providers →
Compare access paths and route side jobs to cheaper auxiliary models.
Telegram Bot Gateway →
Chat with Hermes from your phone via @BotFather integration and secure user ID allowlists.
Skills →
Install reusable workflows from the hub, or let Hermes save its own.
Persistent Memory Architecture →
What Hermes remembers between sessions, and why a new fact appears only in the next session.